ECG-based computer-aided diagnosis techniques and assessment methods are reviewed as a means to improve diagnostic accuracy and reduce costs for cardiovascular diseases.
This survey provides a conceptual overview of ECG-based computer-aided diagnosis systems and their assessment methods to improve diagnostic accuracy and reduce variability.
The interpretation of Electroencephalography (ECG) signals is difficult, because even subtle changes in the waveform can indicate a serious heart disease. Furthermore, these waveform changes might not be present all the time. As a consequence, it takes years of training for a medical practitioner to become an expert in ECG-based cardiovascular disease diagnosis. That training is a major investment in a specific skill. Even with expert ability, the signal interpretation takes time. In addition, human interpretation of ECG signals causes interoperator and intraoperator variability. ECG-based Computer-Aided Diagnosis (CAD) holds the promise of improving the diagnosis accuracy and reducing the cost. The same ECG signal will result in the same diagnosis support regardless of time and place. This paper introduces both the techniques used to realize the CAD functionality and the methods used to assess the established functionality. This survey aims to instill trust in CAD of cardiovascular diseases using ECG signals by introducing both a conceptional overview of the system and the necessary assessment methods.
Faust et al. (Mon,) conducted a review in Cardiovascular diseases. Computer-Aided Diagnosis (CAD) based on ECG signals was evaluated. ECG-based computer-aided diagnosis techniques and assessment methods are reviewed as a means to improve diagnostic accuracy and reduce costs for cardiovascular diseases.
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